Remaining baselines. The remaining baselines employ the same hyperparameters as specified by Hellendoorn et al. [1]}. The Transformer is a 6-layer encoder with absolute position embeddings (512 hidden size, 2048 intermediate size, 8 attention heads). GREAT uses a similar 6-layer architecture with the addition of an edge bias. The RNN is a 2-layer bidirectional recursive neural network with hidden size of 512.
